The
Conversational Interface: The Trigger to Perhaps the Biggest Set of Social-Technological
Changes Today's Adults Are Likely to See in Our Lifetime

This
essay, mostly written in 2003, predicts the near-term (2012 to 2019) emergence
of a Conversational Interface (CI) on the global, mobile, and
wearable web. The CI has also been called a Spoken Dialog System
(SDS), Conversational User Interface (CUI), Linguistic User Interface
(LUI), Voice User Interface (VUI), Natural User Interface (NUI) and other
terms.

For a great easy-to-read book on the machine learning advances that will
soon deliver the CI to internet-enabled devices everywhere in the world,
I highly recommend Eric Siegel's Predictive
Analytics, 2013. If you are short on time just read Chapter 6,
which describes the way IBM's
Watson question answering computer beat the two best human Jeopardy!
quiz show champions in the world in February 2011, answering 90% of
the questions correctly, when earlier versions of IBM machines, competing
in the annual TREC
conferences, could answer only 15% of such questions correctly in
2006. Here is a nice 10 min video, IBM
Watson: Final Jeopardy! and the Future of Watson, 2011, that summarizes
that historic event and looks a little bit into Watson's next applications.

The
Jeopardy! contest was a credibility watershed for the CI, as
it convinced many previous skeptics in the computer science community
that natural
language understanding was solvable by straightforward statistical
and ensemble techniques, approaches which scale quite well as our online
database sizes and computing power continue their exponential
growth.

As many have written since, it now seems reasonable to expect that by
the end of this decade we can expect Watson-like abilities on our wearable
smartphones, and a new
paradigm of teacherless education emerging for all the world's youth
and adults. I believe the social, economic, and political implications
of this emergence will be without parallel in human history, and I've
sketched just a few of them below.

As the primary interface to our species accelerating digital storehouse
of knowledge, the Conversational Interface seems very likely to be the
most important enabling information technology development and collective
intelligence advance on our planet in the next thirty years. Though the
CI will have no self-awareness and very limited self-modeling, it will
have a rapidly increasing contextual (embodied, situated) intelligence,
as it will be 'programmed by the planet' of human users.

The CI will initially be used, as with current information technology,
to foster a variety of new narcissisms, addictions, and dependency behaviors.
First generation cellphones are used irresponsibly by drivers, as the
phones aren't yet smart enough to prevent user abuse (texting while driving,
etc.). First generation video games make kids less aware of and competent
in the physical and social world, as the great serious
games, global games, and wearable games haven't yet emerged, etc.
Yet even the first generation CI will also deliver unprecedented new problem
solving and educational capacities for those cultures, organizations and
individuals who are motivated to use it for positive change, as we'll
describe below.

With its biologically-inspired connectionist algorithms and parallel,
ensemble-based architecture, the CI is a form of artificial intelligence
(AI). Microsoft began working on the AI behind CI's in earnest with the
founding of Microsoft Research
in 1991. But the folks at Google,
just five years old when this article was first written, advanced much
faster and farther in this area, because they were experimenting in the
right area, web
search platforms. Google now seems to have an unbeatable functional
and scale advantage with their leadership in globally distributed search
and archiving, a strategy which will allow a conversational Google OS
to emerge by the end of this decade, and get rapidly more intelligent
every year thereafter. [Nov 2008 Update: See the Google
Mobile App Voice for the iPhone and the new Google
Search Wiki, two big new steps toward the CI. Aug 2013 Update: See
tech journalist Robert Scoble's forward-looking
review of Moto X, Google's smartphone with a dedicated processor that
listens 24/7 to hear three words, "OK, Google Now" to do language
processing for commands to Google
Now, their voice user interface and intelligent personal assistant
equivalent of Apple's Siri].

As we will argue, the CI and its extensions, driven today most centrally
by Google (and of course by all of us, using the world's leading search
platforms), now seem very likely to have a global economic and technical
productivity impact in the 21st century that will greatly exceed both
the emergence of individual and networked computers eras in the 20th century.
Technology
foresight matters, now more than ever before. When Microsoft failed
to recognize in the early 1990's that the CI platform would be far more
likely to emerge in an incremental, statistical, bottom-up fashion via
superior connectivity and organization of the worlds digital information
via search platforms, rather than by some theory-driven top down design,
they permanently lost their chance to sit at the center of cyclone
of the next generation of software systems for social value creation.
They became another victim of the amazingly accelerative, chaotic, and
creatively destructive forces of accelerating
technological change.

When
a cheap, ubiquitous CI and its high bandwidth network and simulation infrastructure
arrives (2015? 2020? 2030?, the exact date seems much more a matter of
social, economic, political and technical choice than destiny), it will
move us out of the Information Age into a fundamentally new era, one that
has been called the Symbiotic Age by some futurists.
This will be a time when all human beings on our planet, including
the currently disenfranchised, functionally illiterate, and marginalized
"bottom three billion," will be able to converse meaningfully
with ubiquitous and semi-intelligent technological systems, and use them
daily to solve a vast range of computationally trivial but very real human
problems. A time when all of us feel truly symbiotic with our digital
appendages. Our digital systems will very likely not be complex enough
to be considered 'organic' within this timeframe, but they will
feel like natural, indispensible extensions to our organic selves.

Most obviously, the CI will help us address the current global inequity
of access to high quality, lifelong education in our increasingly technological
world. And once the digital and educationdivides have fallen globally (eg, effectively 'unlimited'
open source technological education becomes available to any human in
education-permissive societies), the economic and political/
power/ equitydivides can be expected to fall
(or, as social responsibility advocates like to say, move from our currently
transitional/unsustainable distribution, toward more "rationalized"
or "sustainable" distributions) within a generation or two of
the CI's emergence.

There is also good early evidence that CIs will help us discover better
collective solutions in governance, globalization, environment, security,
health, and productivity, among other domains, and allow us to extract
insight and knowledge from all the burgeoning data being collected in
our increasingly transparent and quantified society. The post-CI world
will be an amazing era to be alive, even while it is an era that is still
several decades away from the so-called 'technological
singularity,' the arrival of generally human-surpassing artificial
intelligence in our most advanced computing machines.

A functional CI network will not entail significant machine self-awareness,
but is a transitional stage of advanced natural language processing (NLP),
a field that deserves far greater funding and attention than it attracts
today. NLP advances will combine with critically-needed improvements in
bandwidth of connectivity and the hardware and software of simulations,
so that our CI devices and humanlike agents will "talk" both to each other
and to us, using data-rich semantic protocols, with grammars, vocabularies
and expressions that are continually 'tuned and pruned' by the daily interaction
of hundreds of millions, then billions of humans with the system.

[2009
Note: Most importantly, we need to recognize that NLP advance
is driven 95% by the availability of good, high-quality, semantically
parsable data on the web, and the hardware to store it and networks to
serve it, and only 5% by the effectiveness of any particular
algorithms, software, or computational platforms. In other words, the
CI will be primarily a bottom-up, data-driven, evolutionary emergence,
and only slightly a top-down, engineered, developmental emergence.
This "95% evolutionary vs 5% developmental" emergence pattern
seems to be central to many complex systems emergences, as I argue in
my 2008
paper on evolutionary developmental processes of change.A
quick Google search (using near-conversational structure) shows there
are others who share this critical perspective. As Yorik
Wilks says in David Levy'sRobots
Unlimited, 2006, "Artificial Intelligence is a little software
and a lot of data." Google Researchers Alon Halevy, Peter Norvig,
and Fernando Periera articulate this data-driven strategy for AI creation
quite eloquently in The
Unreasonable Effectiveness of Data, IEEE Intelligent
Systems, 2009. This paper goes a long way to describing how the semantic
web is actually emerging, and shows how what we programmers think
we are doing to make it emerge is usually a lot less useful than finding
better ways to accelerate the creation of big data, to better store, access,
and connect it, to create the digital environment within which our next-gen
CI systems will necessarily emerge. For additional insights on architectural
approaches to the next-generation CI, read Joe
Colannino's2009
Master's thesis (and slides)
on using Statistically Improbable Phrases to automate semantic ontology
creation. Joe says: "Statistically improbable phrases give, on average,
ten times less information overload and more than double the confidence
of retrieving relevant data as compared to Boolean keyword searching.
If the Semantic Web is to become a reality, it will require automated
algorithms such as TF x IDF operating on oodles of data."]

What will a CI enabled browser of 2015-2020 look like? For one thing,
it seems clear that it will soon after include some sophisticated software
simulations of human beings as part of the interface. Already today (2004),
first world culture finally spends more on video games than movies, and
this will apparently be a permanent feature of our world from this point
forward. These "interactive motion pictures" are more compelling
and educating, particularly to our youth, the fastest learning segment
of our society, than any linear scripts, no matter how professionally
produced. [2009 Note: It will also be very visual. Apparently youth under
12 in a few demographics now use YouTube, not Google, as their primary
search engine, so they are visual searchers primarily, text searchers
secondarily.]

Now
imagine that we have begun talking to our computers in a crude but useful
verbal exchange, a kind of 'pidgin grammar' circa 2015. It is
clear that we will not simply want to talk to a disembodied machine. While
some of us will be happy with simple graphic indicators telling us whether
the machine understands us, many more of us will want to relate
to virtual human beings, embodied agents that have the ability to nonverbally
communicate, to frown or place their hand on their chin until they understand
what we are telling them to do, to react with word by word with realistic
microexpressions to our statements and questions, to smile when they detect
we are smiling at their jokes, to act in calm and relaxing manner when
they detect we are upset, to speak more rapidly we are bored or hurried,
etc. Why? Because having a nonverbal quasiemotional communication channel
operating in parallel with linguistic communication makes our
words more efficient and effective. We may not want this for low priority
and multi-tasking communication, but we surely will whenever quality and
accuracy and enjoyment and perhaps even speed are important. Thus we can
see how, over time, we will want our our CI-equipped virtual avatars to
learn to model and display human emotion and body language. We'll want
avatars for the same reason that Webkinz
digitally animated stuffed animals, are so successful with young kids.
We want to relate to our technology. We want our mirror neurons to fire,
we want our empathy activated, we want to feel like our technology
is humanizing, improving its behavior, becoming more intimately connected
to us. [2009 Note: And as soon as it is relating to us in a conversational
way, we'll want to ensure that it's becoming more moral, too. See Moral
Machines, Wendell Wallach and Colin Allen, 2009, for more on
that fascinating insight.]

Given computer technology's far greater rates of innate learning by comparision
to slow-switching biological information processors like us (on the order
of ten millionfold greater, see Chaisson, Cosmic
Evolution, 2001), it is clear that the computers will continue
to adapt to and integrate with us, far far more than the other way round.

The
Digital Twin ("Twin"): Your Emerging Digital Self

Once
we have reasonably good conversational interfaces and semantic maps, circa
2015-2020 in my guesstimation, a major new developments we can expect
at the same time are “Digital
Twins” (DTs or “Twins”), also called personal
software agents (PSAs), intelligent assistants, agent avatars, software
secretarys, etc. that will use these interfaces and maps to construct
crude models of their user’s preferences and values. It's
the user-modeling part that makes these agents into increasingly useful
simulations of and aids for us as individuals. Twins will use as input
user writings and archived email, realtime wearable smartphones (lifelogs),
and verbal feedback, to allow increasingly intelligent and productive
guidance of the user’s purchases, learning, communication, feedback,
and even voting activities, offloading a lot of the information overload
and cognitive overhead of managing modern society from biohumans to their
twin. As I see it, the intelligence amplification that results from our
having twins will begin a major revolution in protecting and furthering
the user’s interests, leading us to a much more democratic society.

Twins will start out primitive, but they will quickly get good at filtering
digital information streams for the user, answering simple questions,
managing simple productivity tasks, and offering simple advice. Many people,
walking in a supermarket or driving on the street, will reach past one
brand of product, or drive past one type of store to another, guided there
verbally or visually by their twin, who is continually using public data,
user history, and algorithms to seek a better statistical match with their
expressed values and preferences. Many companies will build twins, and
we can expect the first generation of these to be given free to you by
major companies and heavily manipulated by marketers, but it is also clear
that companies with the best records of respecting privacy and empowering
users will quickly become the most popular. Open source versions of twins
will be built by who distrust the corporate versions, or wish to maximize
user control. [2013 Note: Decentralizing technologies, like Twins, that
empower people to both make better personal and collective decisions,
to maximize their future
freedom of action, seem very likely to increasingly dominate over
processes used to maintain traditional hierarchies, in all market economies
in coming decades. Decentralizing processes break down old hierarchies
and allow new, better adapted ones to reform in their place. Consider
the great flattening of corporate hierarchies that occurred with the introduction
of the personal computer in the 1980's. Consider also the way Comcast's
Xfinity and other tired monopolies will soon be disrupted by the arrival
of true internet television as soon as we all get near-gigabit broadband,
as
I've written elsewhere.] Many people will allow their twin’s
record of their preferences to be at least partly public, so that other
individuals, companies, and groups that share their preferences can easily
find them. Sharing and modifying preference files between twins will be
automated or manual, as desired. Ads will be more personalized, and useful,
than ever before.

Companies and governments that don't respect user preferences will increasingly
be constrained by the shifts in consumption patterns and in initiative
politics that will be coordinated by networks of individuals, using their
twins to keep track of what kinds of purchases and votes and initiatives
will best support their values. This is a level of invididual empowerment
that the web has always promised, and which will finally be delivered
once we cross a threshold of intelligence amplification for the individual
voter. Why will many, and eventually most of us run twins? Because we
want a smart and highly personalized extension of our own memories and
desires, one that will increasingly represent and motivate
us, and that can increasingly act in more uniquely differentiated and
creative ways.

Twins will guide us to purchase from the most socially responsible, innovative,
and consumer responsive of the corporations, and to back the most democractically
advantageous initiatives in politics, chaining our corporations and the
governments they have captured to a virtuous cycle. We have allowed our
corporations in particular to concentrate wealth and power vs. all other
actors for roughly the last century, and to prioritize growth over the
common good. They have been aided in this slide to inequality and plutocracy
by our first generation of communications, media and computing technologies,
which are mostly "one to many" (hierarchical). Voters will increasingly
get their power back in the "many to many" media world now emerging,
but the greatest advance will be twins, as they will function as electronic
augmentations of our own power in democratic states.

The rise of twins will shift the tide back to a more representative democracy,
with less crony capitalism and greater economic equity (see Daron Acemoglu's,
Why
Nations Fail, for more on the costs of weak instititutions and
too large an internal rich-poor divide). In America, we've had increasing
rich-poor divide since the early 1960's, so if the reversal starts to
happen in the 2020's, as I suspect, it will have been 80 years coming.
Political and economic activities will likely still be corrupt at the
very top, and with the very rich. See Lee Kuan Yew's, From
Third World to First: The Singapore Story, 2000, for a great
(and self-deprecating) story about how he was able to eliminate corruption
at the mid-levels but had no power to eliminate it at the top in his modernization
of Singapore. But as long as most of the system works for most
people, our incredible record of scientific and technological acceleration
will continue. All the world's powerful actors will increasingly be constrained
in a global democratic and transparency cage, and we will move even more
quickly toward a postbiological
and far more ethical world.

I expect we will see such a world by the end of this century, so we may
not have long to wait before we permanently and irreversibly leave the
era of unaugmented biological humans running politics on Earth. Increasingly
postbiological intelligence will very soon emerge on Earth, whether we
want it to or not, and that's going to be a very different world. For
some thoughts on what that world will look like, I recommend Robert Wright's
Nonzero,
2001, Ray Kurzweil's The
Singularity is Near, 2006, Wendell Wallach's
Moral Machines, 2010, and Bowle's and Gintis's A
Cooperative Species, 2011. Books like these make clear that humans
strive for accelerating positive-sum returns and the common good in general,
and that money and power is corrupting mainly at the top, less so among
the many. Furthermore, if our best AIs are going to be built by starting
with scanned human mental patterns and computational
neuroscience, as many of us believe is the fastest and most reliable
path to AI, then they will start out with our level of morality
as a base. And if morality is a function of individual and social complexity
at playing positive sum games, as I believe it is, our intelligent machines
will rapidly exceed us in their moral capacities and behavior. There are
a lot of "ifs" in this scenario, but I challenge you come up
with one that better accounts for humanity's record of ever accelerating
complexification, in an universe that seems biased to growing the leading
edge of planetary intelligence from physics to chemistry to biology to
biominds to technominds over time.

Additional scenarios for the future
of twins can be found in my 2010 video, The
Digital Self, and in philosopher
Eric Steinhart's Survival
as a Digital Ghost, Minds and Machines, 2007, 17:261-271.
In particular we must understand the rationale for some of us to want
a twin, as opposed to just a very good butler or servant, with its own
separate personality, as many of us will choose butlers instead, at least
at first. But as systems theorists Roger Conant and W. Ross Ashby argued
in 1970, every
good regulator of a system must be a model of that system. As our
digital twins become better and better regulators of our biological selves,
regardless of their initial personalities, they must become increasingly
better models, extensions, and twins of ourselves.

At some point, we may learn how to merge even our higher
thought with them, via brain-computer
interfaces, and should that occur we would consider them an indistinguishable
part of us. At that point, when our biological bodies die, this should
subjectively feel, to our digital-biological hybrid self, simply like
further growth and change, not death. This is speculative of course, and
if you want more on that, visit the last section of this article below.

In the 1980's, technology futurist George Gilder talked
eloquently about the Microcosm,
the explosion/new environment/universe of inexpensive microprocessing
power, which began in the 1960's, and ushered in the personal computer.
In the 1990's he talked about the Telecosm,
the explosion of inexpensive telecommunications via fiber optics and network
technologies, which began in the late 1980's and ushered in advanced new
forms of globalization. Futurist Bruce Sterling, in Shaping
Things, and technologists Chris Stakutis and John G. Webster
in Inescapable
Data, have each talked about the Datacosm, the explosion
of unstructured data on the web, which began in the late 1990's and has
led us to fantastic new automated structuring tools like Google, and new
data mining and competitive intelligence platforms.

In the early 2000's I began thinking about next steps
in this hierarchy, and became interested in something I call the Valuecosm,
the explosion of structured public and private maps, data sets, and statistical
models of human preferences and values. We can think of the valuecosm
as an element of the Semantic
Web, that eloquent vision of Tim Berners-Lee, but focused most specifically
on human values and preferences in a broad variety of contexts, and graph
theory, Bayesian, and other models comparing those values quantitatively
and qualitatively to others in the values space.

In concert with digital twins as our interface to the
digital world, the emerging valuecosm will help us grow avatars that act
and transact progressively better for us every day, will lead us to dramatically
better discovery of potential positive-sum social interactions, to better
and more distributed social network media and education, to great new
subcultural diversity, and and ultimately, to new ways to hold powerful
actors accountable to democratic values.

In this way, as our digital twins begin to approach human
level sophistication later this century, we will use our them to look
after our values and advise us on our votes, purchases, and collaborative
behaviors ever more powerfully, and thereby usher in a new level of
global accountability of corporations, institutions, governments, and
other large actors to human rights and democratic values. This will
be the first generation of an era of total
systems quantification, of both abstract and concrete issues of human
value, to use futurist Alvis Brigis's excellent phrase, and perhaps the
first advanced version of the digital
democracy vision. See The
Valuecosm, 2004 for more of these longer-term arguments,
if interested.

Once we have reasonably good values maps on the web, and
a reasonably advanced twins, able to scour the web for us while we are
asleep, to act as our message and media screener and butler while we are
awake, etc., imagine the positive implications for:

Subculture diversity and representation (great new
experimentation in victimless variety)

Global communication and collaboration (no language
barrier)

Global digital divide (nearly disappears)

Accountability of powerful actors (automated lobby twins for every
group with votes and values maps)

As I've argued with my tongue-in-cheek Fourth
Law of Technology, we must also expect, and try in advance to minimize,
all kinds of first-generationproblems
with these technologies. Consider for example some of the first-gen downsides
and concerns digital twins and the valuecosm might bring to:

Data security and privacy

Crime and fraud

Predictive marketing and consumer behavior programming

Public relations manipulation

Echo chambers/cocoons that polarize and lose touch
with external realities

Parenting (how early can kids have DTs?)

Getting past the dehumanizing effects of these disruptive
technologies that are inevitable in their first generation, moving on
to the neutral effects of the second and finally the positive effects
of the third generation and beyond, will be major challenges for designers,
early adopters, critics, investors, entrepreneurs, politicians, and the
other key players in our multifaceted society.

Using Pareto's
Law, I would grossly predict that 20% of us will end up using twins
and the valuecosm for net personal empowerment, to take us to amazing
new levels of innovation, and to just-as-amazing new levels of collective
ethics and sustainability. In other words, 20% will of us will use these
tools to be measurably better and more self-empowered than our parents
were, on all the measures that matter to us.

At the same time, the other 80% of us may well choose
to use these tools for new levels of fantasy, entertainment, distraction,
and domestications. I don't think we have to worry so much about that,
as long as we keep our citizens away from the worst of the new addictions
and dependencies. As long as we don't let these citizens slide into ignorance,
thereby creating an Idiocracy, or allow our use of these tools to cause
structural
violence, a term coined by futurist Johan Galtung.

In
other words, as long as the 20% of folks who get the 80% of the work done
in any society (Pareto's "Vital Few") are significantly empowered
by these platforms, everyone else can take a long-deserved rest from millennia
of toil, brutality, and hardship, for as long as they want to, in fact.
So it's a "both/and", bimodal world we are headed toward. 20%
of us will choose to get more empowered and 80% will likely choose more
slack, entertainment, and distraction. The liesure
society that emerged in the 20th century, so well articulated by futurist
Herman Kahn in the 1960's, will continue its inexorable advance to new
heights of comfort and domestication in the 21st century. Nevertheless,
I'm quite convinced that we are not going to see an idiocracy
emerge, at least for the next few decades. The 20% who are the
opinion leaders and political and economic movers and shakers will be
compelled to ensure that the 80% are free enough and educated well enough
to be civically minded and personally responsible for some measure of
their own social advancement. If they don't address this problem, the
80% will vote itself ever increasing financial and social entitlements
every year outstripping the real wealth and productivity of the nation,
and those democracies (think of Greece, Portugal, Spain, etc.) will quickly
slip into financial insolvency, while the more technically productive
and evidence-driven democracies (Scandinavia, Germany, Switzerland, Singapore,
Taiwan, South Korea, etc.) will surge ahead as new leaders.

One could argue, and many have, that the United States,
with its fifty years of rich-poor divide growth and increasingly poor
K-12 education system, is in danger of becoming an idiocracy in the next
generation or two. But the truth is, today's youth are far smarter than
that, and the CI, teacherless education, and the symbiotic age will emerge
far, far sooner than any real idiocracy could arrive in the U.S.

We can do our best to improve our very slow moving, inertia-bound
political and economic systems, but if we are to learn the universe's
lessons of accelerating change, we must roll up our sleeves and focus
primarily on building the continually accelerating scientific
and technological systems that will deliver a far more democratic values-driven
and teacherless education world. Everything else but our science and
technology, and our interface to them, is so slow moving and growing
as to be nearly future-irrelevant, by comparison.

Predicting
the CI Emergence

When can we expect the CI's emergence?In March 2005 Google's director of search Peter Norvig noted
that their average query is now about 2.5 words per query, by comparison
to 1.3 on Alta Vista in its heyday, circa 1998. In subsequent email conversation
with him he has told me that the actual number is "closer to 2.6
or 2.7." This is an initial doubling time of only seven years, if
this is a quasiexponential function.

It appears that the growth of the CI as a
complex adaptive technological system is in the early phase of an S-curve,
well before the inflection point, and thus its growth will continue to
look exponential for some time to come. [September 2008 Update: Average
query length to Google now exceeds 4 words, apparently
just this month. This is more early evidence that this phase of search
query length growth will remain exponential up to the inflection point.]

In my opinion this average search query length,
averaged across all the leading search engines of the day (Google, Yahoo!,
Bing, etc.) will be one of the key numbers to watch to gauge the growing
effectiveness of statistical natural language processing (statistical
NLP) in creating a conversational front end for the internet and all our
other complex technologies in the 21st century.

A presentation from one of my technology foresight slide
presentations below attempts to summarize this point:

How long might the emegence of a full-fledged
CI take? That's a big guess today, but given that it has taken approximately
seven years to double from 1.3 to 2.6 words per average
query, we should expect another seven years, circa 2012,
to get us to 5.2 words, a period I suspect would be just priorto
emergent grammars and the feeling of CI intelligence
(something "semismart" on the other end of the line) on the
part of the user. If these proposals and qualifiers
are approxmately correct, this would place the intelligent CI's
emergence circa 2015-2020. [2008 Note: One could even
argue that our very first generation (slow and very limited) CI has finally
emerged with Google
Voice on the iPhone in 2008.]

[2010
Note: The Nexus One,
Google's new android phone, is another amazing step forward in pairing
the emerging conversational interface with very humanly useful functions,
such as turn-by-turn navigation. As you may recall, the
replicants in one
the greatest sci-fi films of the 20th century, Blade
Runner,
were Nexus Sixes, near-human androids, but with an engineered four-year
lifespan. Kind of like phones, if you think about it.:) How long will
it be before we are wearing a Nexus Six? How long before our Nexus DT
is smart enough to pass a Turing/Voight-Kampff test as human? How long
until your twin becomes a good representative of you? Think I'm joking?
Don't bet against it!

When
the Nexus One is combined with Siri, a powerful new NLP
and AI plugin available for the iPhone today, and for the GPhone soon
(according to the grapevine), the conversational interface will take another
important step forward. Take a look at Siri,
it is smarter than you probably suspect, and a great potential acquisition
target for Google. Here's hoping they get acquired, we'll see. [2010 Note:
We know what happened here, Apple, not Google, made the aquisition, so
Google had to play catchup.]

English speakers appear to use an average
of 8-14 words per written sentence and 5-11 words per spoken sentence
(depending on context) when we ask each other complex questions. I would
expect that as soon as our average search queries get up over
eight words a sentence, if not before, we'll start to see and
expect emergent "pidgin" grammars in our computer's responses.
Since voice recognition and text to speech are alreadly largely solved
(they are far easier problems to solve than NLP), we'll be speaking and
listening to to those sentences. At that point, we'll begin to feel like
our computers have a primitive conversational intelligence.

[2008 Note: Google's announced a voice recognition
app for the iPhone this month. A NYT
article on Google's Voice Technologysays their statistical
model (unique words and some of the ways they can be strung together to
ask common questions) is composed of two trilliontokens
(unique words and word combinations). Having this application available,
even if it is used only for simple queries for the next few years, should
easily push the average queries past four words, as it is far easier for
the average person to speak a longer sentence than to type one.
And Google
Search Wiki, if it is used extensively, promises another advance toward
buiilding a statistical map of words that should be strung together to
answer human questions. Google is starting with just a personalized version
of your search results, but they will clearly eventually release collectively
aggregated and friend aggregated versions as well.]

[2005 Note: Already today, when you use "near"
in a sentence on Google, as in: "Coffee shops near Palo Alto",
which returns a Google Map (yay, Google's now got an optical cortex!)
of yellow pins, all distributed around Palo Alto's city center, you are
using a query length of four or five words. But this doesn't yet feel
like conversational intelligence.] That's where I suspect we'll be in
2012, a lot of folks using a lot of simple verbal operators but probably
still mostly by keyboard [2008 update: With the release of Google's app
for the iPhone this year, it seems possible that voice queries might begin
to rival keyboard queries by 2012, as there are so many more phone users
than computer users. I'd love to see an internal projection for that].

Now step forward another seven years, to
2019, and in my estimation we will likely have doubled our search
length yet again, to just over ten words per average query.
Somewhere between 2012 and 2019 I expect we'll see voice recognition queries,
most of them mobile/wearable, begin to compete with keyed entry for human-to-machine
communication, and a new level of sophistication (and user feedback/ranking/rating)
of the average queries. This time, I think we have enough new functionality
to create a"step function" in user experience, where the web
no longer feels like just an information appliance, it now feels like
a partner, a crude extension of our linguistic ability. That's what I
would call the end of the Information Age and the start of the Symbiotic
Age. From that point forward many of us will begin to feel naked
and somewhat stupid out in public without the web, the way we'd feel out
in public without our clothes today.

What is our evidence that this query length
doubling will continue? It's weak today, but I think still worth watching
closely. First, consider that seven years per doubling would be just over
the six year doubling in average software productivity or general algorithmic
efficiency quoted by Bill Joy and others in the IT industry as a rough
"Moore's law for software." But doubled algorithmic power or
efficiency alone would be unlikely to translate to doubled query lengths.
We will need a lot more insight before we can make this claim.

My main intuition in this regard is that the entire human
conversation space (the space of most useful human conversations, regardless
of context), while still very much larger than our digital record of it
today, is becoming an effectively 'closed' (slow growing, nearing saturation)
phase space, what the physicists call 'ergodic', and furthermore that
the encoding of human conversation in easily spiderable form is doubling
in volume at an enormous rate by comparison (roughly every two years,
since the start of the web), and that our ability to rank the relative
value of those encodings is also steadily improving (Google's PageRank,
Web 2.0, 3.0, etc.).

In other words, I suspect that the human conversation phase
space, in all languages, and all digital forms (web publishing, email,
audio, video, chat, and other searchable conversations) while still growing
slowly in novelty, is becoming effectively, approximately, or statistically
computationally closed relative to the rapid mapping of this space by
technological intelligence. If this is so, all the most useful and functional
thoughts/ideas/sentences in the human mind space are increasingly frequently
revisited by technological indexes. The 'map' grows only slowly relative
to the 'mapmaking,' which gets finer-grained every year.

If this is true then the hard problem of serving up a useful,
semi-intelligent natural language response to an online query is very
much like codebreaking, a cryptographic problem that
involves finding the set of primers, or translation elements, that are
repeatedly used to transform one set of information into another. For
the CI, this is the transformation of the world wide web of digitally
encoded symbols of use to human beings, into another, the most useful
linguistic responses to queries about common human problems. At the same
time, new intelligence/information emerges through the associations made
during the translation. Codebreaking, like many natural growth processes,
follows a logistic curve (an S-curve) in performance over time. Early
in the process (the first 'flat' part of the S-curve) it's hard to get
the primers. Then you enter into a positive feedback situation where you
are getting the primers for the most used words (the 'fat head' of the
Zipf's law distribution) and that makes it easy to decode the other high-frequency
words. Then you hit the inflection point, having gotten most of the easy
words, and you start chasing after increasingly less used words, with
less reliable associations to other words, and you've hit the phase of
declining returns (the 'top' of the S-curve, saturation, system 'senescence'
in performance). But in the first phase of growth, before reaching the
inflection point, the performance growth is roughlyexponential.

I suspect the saturation point in query length will come
at some sentence length that is slightly longer than the average human-to-human
query length in spoken sentences. I suggest this because when you query
Google, it is often to your advantage, even when asking technical questions
today, to include additional words beyond those you'd normally ask any
human in natural conversation. You use those specialized words with Google
because you suspect (and it is increasingly true) that Google knows "everything,"
unlike the average human.

If 2020 is our expected transition point, as has seemed
most likely to me since first thinking about this issue circa 2000, then
CI's are a bit farther off than some of our most optimistic technology
futurists would today have us believe. Yet they are also much sooner arriving
than the naysayers predict, those who tell us NLP is riddled with near-insoluable
problems, and who don't understand how far we've advanced already with
simple statistically based systems.

I have heard that Google, for example, has won U.S. NIST's automated
language translation competition, over IBM's and other's ontological and
mixed systems, by using a relatively simple statistical NLP approach (tied
of course to a large and ever-growing online corpus) for at least two
years in a row (2005 and 2006).

With leadership, luck, resolve, and exponentially more powerful computing,
text analytics, and comunications platforms, we might even be able to
accelerate CI development to occur even earlier than the 2020 ETA. In
addition to broadband and wireless acess for everyone, I suggest that
may be one of the noblest challenges of our generation, in fact.

Annually for the last six years, John Brockman's provocative World
Question Center at Edge.org has
posed an interesting question to roughly 100 edge-thinkers who are committed
to integrating both scientific and humanist perspectives on the world.
In 2002, they answered a fictional letter from then-President G.W. Bush
which asked each of them, as the administration's new science advisor,

"What are the pressing scientific issues for the nation and the world,
and what is your advice on how I can begin to deal with them?"

As a developmental futurist, one who expects that a special subset of
future events are statistically inevitable and highly predictable, I drafted
and sent John my own unsolicited response below.

Clearly the keyboard is a primitive, first-generation interface to our
personal computational machines. It gives us information, but not symbiosis.
We humans don't twiddle our fingers at each other when we exchange information.
We primarily talk, and use a rich repertoire of emotional and body language
in simultaneous, noninterfering channels.

We also use our hands to help each other and to manipulate objects ever
since the first stone was thrown by the first hominid, so it is also clear
that keyboards won't disappear until the human form itself disappears.

In other words, talking is the highest, most natural, and most inclusive
form of human communication, and soon our computers everywhere will allow
us to interface with them in this new computational domain. I think that
achieving this emergence will be one of the greatest of all the technological
"Moon Shots" we engage in during our own brief time here on
Earth, whether we presently realize it or not.

Science and technology, and broadly, local computation, appear to be
asymptotically accelerating, universally-driven phenomena. We are now
coming to understand that humanity does not control this developmental
process, but rather selectively catalyzes it, ideally
with ever increasing social, organizational, and personal foresight.

The entire 20th century demonstrated an astounding, unrelenting, unprecedented
double exponential growth in the price performance of our computational
machines. At the same time, we have seen new levels of computational autonomy,
or human-independence emerge, wherein a rapidly diminishing fraction of
human effort is required to produce any fixed amount of computational
complexity within each new computing system. These are apparently universal
developmental trends, not architected by human design or even desire.
For the last decade at least, increasingly evolutionary and biologically
inspired forms of computation have become the leading edge of technological
development, and will remain so for the foreseeable future.

Referring to the difficulty of technology prediction, Bill Gates reportedly
once said "find me the person who predicted the internet, and we'll
make him king." This is congruent with a common myth that futurists
missed this major development, and certainly many did. The first major
"think tank" long range public futures project of the postwar
era, The Year
2000: A Framework for Speculation on the Next Thirty-Three Years,
Herman Kahn and Anthony Wiener, 1967, certainly missed the decentralization
trend, though they did see computing continuing to accelerate. But that
only shows the riskiness of relying on one forecasting group to understand
the future. Every community has its own biases.

Among the global community there were numerous visionaries who foresaw
various pieces of the internet long before it emerged. In 1937, H.G. Wells
in "World
Brain," articulated the developmental inevitability of a rapidly
updating compendium of total world knowledge. In 1945, in "As
We May Think," Vannevar Bush proposed the Memex,
a proto-hypertext microfiche network that would organize and distribute
the world's knowledge, and noted "The advanced arithmetical machines
of the future will be electrical in nature, and they will perform at 100
times present [electromechanical relay computer] speeds."

In 1946, just one year into the modern
television era, Will F. Jenkins (aka Murray Leinster) in "A
Logic Named Joe," predicted "logics," televisions with
attached keyboards that were networked by a switching innovation called
the "Carson Circuit," that would be used to watch TV, make video
phone calls, send and receive telegraphic messages (email), get weather
reports, ask research questions, keep books, trade stocks, and play games.Sound like the internet to you? Sure does to me.

The emergence of personal computers was repeatedly predicted by journalists
and commentators in the 1950's, and were a longtime goal of electronic
hobbyists, who were making successively more complicated home built electronic
systems. Peter Drucker predicted our 1980's economic shift to the information
economy in the revolutionary Age
of Discontinuity, 1968. Alvin Toffler expanded on this and the
coming network of "electronic cottages" we would see in the
1990's in The
Third Wave, 1980.

In other words, there were many harbingers of the internet for those
willing to look, and those who realized that trends in miniaturization,
computing, and communication would have to continue to accelerate, because,
borrowing from the biological lanaguage of evolution and development,
they weren't just evolutionary choices, these particular trends
were developmental forces that the universe (our extended environment)
was imposing on modern society.

Because most change that occurs in the universe is evolutionary,
I believe prediction is generally quite difficult, particularly for those
who don't discriminate between evolutionary and developmental dynamics.
But developmental processes, when they can be discerned,
are surprisingly easy to predict. In the language of complexity studies,
they are 'standard attractors', like the hole at the bottom of a basin,
or fitness landscape. You cannot predict exactly how the "marble"
(the system, evolution, us) is going to get to the bottom of the basin,
that is an evolutionary uncertainty, but you know all the evolutionary
marbles in the system go through one of the few developmental "holes"
available.

To recap, there appear to be two fundamental processes of change at work
in all universal systems: evolution and development. The
coming CI appears to be, as far as I can determine, a developmental emergence,
and we can even measure it's progress, speculate on its enabling and inhibiting
factors, and even predict its arrival from past progress, should we choose
to do so.

The CI network will not replace the keyboard, as
some futurists have incorrectly claimed. For those who today have the
education and resources to learn them, keyboards are powerful extensions
of human will into the physical space. They will continue to increase
in prevalence and sophistication, and will be with us as long as we continue
to have biological bodies with ten fingers. Nevertheless, at the same
time we can expect that most human computer interaction will move beyond
the keyboard, and the ease, power, universality, and sophistication of
the CI network will make all our technologies embodied, egalitarian, and
symbiotic as never before.

In an evolutionary developmental universe, many evolutionary paths are
within our control, challenging us to be good stewards and navigators,
but some developmental destinations, such as accelerating local computation,
are apparently not, challenging us to be good cartographers, prioritizers,
and students of physical dynamics. This phenomenon of continual acceleration,
also known as acceleration
or singularity studies, is in need of much greater scientific attention.
We will almost certainly see the CI network's emergence within our own
lifetime. Perhaps the most important remaining questions are how soon,
how balanced, and how humanizing will be the path we take toward it.

More
CI Details

Fifty years ago, the advent of digital computers moved us from the Industrial
Age to the Information Age. But the information age is now
getting on in years, and we will soon need a new phrase to capture the
meaning of a coming environment where the average human interaction with
the average computer is not via keyboard, but by voice. I and others have
suggested that the Symbiotic Age is the most appropriate term for
this coming era, as it will describe the dominant zeitgeist of the experiencea
time when human beings finally feel both significantly empowered by and
inseparably connected to their technological infrastructure. A time when
anyone on the planet who is comfortable with talking will be cheaply and
intuitively connected to the machines around them, when we will start
thinking of and talking to our machines as physical entities, flexible
to our needs, when complaints and compliments that we have will be relayed
to appropriate parties, when the user's vocalizations will be an integral,
and eventually, dominant part of the utility of our technology.

Circa 2015-2025, several forecasters expect our natural language processing
(most difficult), bandwidth accessibility (less difficult), human simulation
and language translation software (even less difficult), and voice recognition
software (already here) to each be finally sufficiently powerful, affordable,
and ubiquitous that a new type of interface will emerge. Around this time,
the majority of human-computer interaction on our global computer network,
however we choose to measure it, will shift to a new level of sophistication.That new level will be the move from our present simple keyboard-
and mouse-driven, primarily graphical user interface (GUI, or "gooey")
into a graphically based, sophisticated mouse and keyboard (including
virtual keyboard) utilizing, but primarily conversational interface (CI).
A somewhat different definition of the CI's arrival involves that point
where the majority of code and hardware behind the average computational
interface is designed to interpret human language and intent.

This is the most difficult interface problem presently known,
more difficult even than constructing realistic virtual graphical environments,
where great and accelerating commercial success (e.g., video games) has
occurred over the last decade. CI-era network machines, tools, and services,
including educational services, will not simply exist to serve us web
databases and graphics, as they do today, but to empower a vast range
of intelligent, linguistically guided human-computer interactions, in
an organic technological environment where the average human command to
the network is delivered verbally, not physically (as via punch card,
keyboard, mouse or other physical input device). Think of the opportunities
for human development!There are so many new skills, empowerments,
services, and products that will evolve from this new capacity that we
may rightly consider its full benefit difficult to imagine.

There
have been a number of impressive early starts at spoken dialog productivity
platforms, like Virtuosity's automatic speech recognition (ASR) voice-activated
telephone assistant, Wildfire,
a promising but failed commercial effort in the early 2000's, and there
are emerging web standards, such VoiceXML.
See Wikipedia's entry on Dialog
Systems for recent developments. There are promising basic research
efforts, such as Microsoft's Natural
Language Processing (NLP) Group, the consultancy SRI International
(they have a 50 person Artificial Intelligence
Center) and NASA Ames, who have developed third generation voice recognition
systems now able to identify emotion, punctuation, and other higher level
meaning from the prosody
(variable pitch, timing, loudness) of a voice stream. SRI's Elizabeth
Shriberg projects that software with the ability to extensively decode
prosody, as well as to reliably filter out background noise from any real
world voice stream, will arrive circa 2012.

The continued development of better "top-down" computing standards, such
as Tim Berners-Lee's/ W3C's semantic
web, will be a part of this process. But the major part is likely
to be evolutionary developmental and "bottom-up," like Microsoft's MindNet
project, involving the integration of ever-smarter artificial neural networks,
or their biologically-inspired equivalents, into the "back end"
systems running all the tools and technologies we use. Even today, users
of early CI systems (directory assistance, flight reservations, etc.)
increasingly look forward to each hassle-free upgrade of the back end.
Compare this with the mixed feelings we have toward user-guided upgrade
processes, and the emerging human-machine symbiosis becomes tangible.We
will all play a part, unwitting or not, as this drama unfolds in these
final years of "unnatural interface."

On
Phase Change Singularities: The Nature of CI Emergence

Circa 2020, we may expect a highly useful set of CI-equipped interfaces,
built on top of an increasingly parallel but still weakly biologically-inspired
set of computer architectures. The CI seems a necessary prerequisite
to high-level machine intelligence. Therefore, understanding
and measuring the process of CI emergence may give us insight into the
dynamics of the technological singularity (generally human-surpassing
machine intelligence) to follow.

Why can't some gifted and motivated individual, or perhaps a massive
team of individuals (say, Microsoft
Research) create an adequate CI using mostly top-down rationally guided
design, working in relative isolation from the rest of the communications
activity of the planet? Such systems have been tried many times before,
and they have predictably been far less valuable than their designers
expect. Instead, a much more distributed system transition may be necessary
for the CI to emerge.

How must the "Symbiotic Era" of the CI emerge? I'd expect through
a massively distributed computational and information storage system that
records and analyzes the entire human conversation and behavior space,
in all the major spheres of human interest and experience. Furthermore,
this system must first conduct multifold creative evolutionary experiments
to attempt to construct meaning from this conversation, and in this process
a small developmental subset of highly useful natural language processing
systems will be created. The emergence of these systems will not be sudden
or isolated, but incremental and global, as they are guided and pruned
over many years of continuous human conversation with them all across
the planet.

How far are we away from being able to create the next generation of
such a system? I suggest you watch the development of the current generation,
the planetary internet, to search for signs of the CI's emergence. Today,
roughly seventy percent of the 200 million daily verbal queries that Google
(the most popular search engine on the planet) receives are novel. I have
heard thatUrs Hölzle at Google wrote a thirty day user query
cache circa 2000 but it was not useful, much to the surprise of the company.
Too many of the queries at the time were new and unpredictable to the
system. When leading search engines begin to cache and do natural
language processing on their user queries because most of them are
repeating (circa 2015? 2020?), we will know that the human linguistic
space has started to become ergodic (a well-explored and frequently repeating
phase space). Soon the entire human preference set as expressed in written
language, will be, to a first approximation, cataloged and monitored in
real-time by our distributed network of computing machines.

This is a form of effective computational closure, a necessary
precondition for a phase transition singularity (the CI emergence) to
occur. Presently there are at least two problems preventing this evolutionary
developmental emergence. The first is that there is not enough memory
available to the cache (not simply the last thirty days, but something
approaching the entire written history of human inquiry needs to be cacheable
by our technological systems, something we can't expect for another decade
or two). The second is that there probably is not yet enough global users
on the system. Google's 200 million queries/day in 2003 were generated
by only a few hundred million regular computer users. As responsible globalization
advocates remind us, it is probably safe to say that these users are not
yet sufficiently representative of the full interests and inquiries of
the six billion people presently on the planet.

You may have heard that Microsoft is recently (2004) launching a major
new search software development initiative. This will be critical to the
long run economic success of the company, because verbally-driven search
is the first generation conversation of humans with machines. It is within
the search space that the intelligent internet, and the next generation
CI-based operating systems will emerge. Windows 2020 (perhaps better renamed
Conversations 2020) will have to be built on such a platform, or
Google-like systems will outcompete them for average human use.

Google is becoming a truly unique distributed data processing platform
("GooOS"),
and may well in coming years encode a full-featured operating system as
an afterthought, rebuilding Windows functionality in a linguistically-driven
Google language. Microsoft will have to match Google's distributed CI-based
functionality in coming years. To not do so would be to risk being late
to the next major reinvention of the planetary computing platform. As
futurists Mark Finnern and Wayne Radinsky both note, Rich Skrenta'sexcellent post "The
Secret Source of Google's Power," relates that Google's competitive
advantage springs from the features of its hardware network. It is developing
a distributed computing platform that, in 2004, "can manage web-scale
datasets on 100,000 node server clusters. It includes a petabyte, distributed,
fault tolerant filesystem, distributed RPC code, perhaps including network
shared memory and process migration. And a datacenter management system
which lets a handful of ops engineers effectively run 100,000 servers."
That's some impressive automation.

Another way to understand the emergence of the internet-based CI is
to explore the historical developmental phases of web search technology:
1) The first wave of web search was created by cheap disk drives (Altavista
won this war) 2) The second wave has been created by cheap CPU's and Beowulf
cluster networks (Google won this war) 3) the third wave, cheap RAM, may
be the next inevitable emergence. Cheap RAM will make both massive fast
caches and new, far more complex CI-based algorithms possible. Who will
win the third wave? That is an open question, at present.

All of this is not to suggest that human learning will decrease as we
approach and enter the CI-enabled Symbiotic Era. To the contrary, our
learning will clearly be shifted to a whole new level as all kinds of
new collaborative and creative opportunities emerge in CI-driven real
and virtual space. I expect the CI to enable our currently laughable
digital avatars (digital persona, or "digital me" (DM)) to become
both increasingly accurate reflections of the sum of our aspirations (e.g.,
Lifelogs) and increasingly effective coaches and couselors of our higher
selves. Post 2020, I expect my DM will begin doing things in virtual space
that are amazing by comparison to what I am doing in physical space. For
a fun fictional account of the Symbiotic Era, see my teen-oriented essay
"Future Heroes 2035: My Friends
and I."

It helps to realize that the biological portion of human species activity
is sharply limited by the fixed number of us (6 billion) and fixed speed
(200 miles/hour) of communication within biological brains. From the perspective
of computers that are growing their capacity exponentially, and learning
and recording million times faster than our own brains do (on a range
of measures), the entire human phase space appears essentially frozen
in spacetime. Capture, closure, and convergence between humans and our
digital extensions are the dominant features we can expect, from our perspective.
(Things look much more exploratory and dynamic from the perspective of
the machines).

In the Symbiotic Era, a time when higher machine intelligence can exist
only as a first-level reflection of human aspirations, the most important
feature, for planetary intelligence, will be the "Intelligence Amplification"
(IA) that increasingly powerful, CI-equipped systems provide to humans
who are using them everywhere. I'm presently assuming this era will comprise
30 years, from 2020-2050. That would place the arrival of the next singularity,
the Autonomy Era, circa 2050. The latter era would involve the emergence
of initially simplistic but eventually strongly biologically-inspired
self-improving systems. Because I think such systems must gain their self-awareness
through a process of personality
capture and co-evolution with human beings, I expect they too will
require a nontrivial length of time, in human years, to develop truly
complex personalities. This might take perhaps ten human intelligence
years, though this would represent a far longer stretch of time in machine
intelligence years. That progression would fit with a circa 2060 technological
singularity (a developmental "phase change" involving the
emergence of human surpassing technological intelligence).

Intelligence amplification (I.A.) systems like the CI network are highly
collectivist in their construction, and will be tested and refined by
an entire planet's worth of users. They are also highly symbiotic, and
will engage in extensive profiling, simulation, human factors internalization,
and "personality capture" of their users' behaviors, habits,
goals, limits, and rational and emotive states. As our second-generation,
post-2020 CI systems increasingly use personality capture techniques
to build sophisticated world-models of their users, we may expect that
an increasing number of human beings will give their semi-intelligent
agents access to and influence over their mind states in an always reversible
but progressively more intimate manner. Most accurately, this should be
considered a true first-generation form of "uploading," predating the
more intensive and invasive forms of uploading that will occur in subsequent
iterations of the symbiosis.

Will you choose to let your 2030 machines cheer you up, advise you on
your interaction style, or tell you when to take a work break? Today there
are robotic toys (AIBO, smart dolls) that already program their users
to provide specific emotional responses. The tremendous utility, comfort,
and productivity of CI's utilizing personality capture and more specialized
tools such as knowledge management (a first-generation electronic forebrain)
will compellingly demonstrate to millions of modern skeptics that the
developmental destination of human-machine interaction is not some dystopian
scenario of computer domination or isolation, but instead an increasingly
seamless and symbiotic convergence.

After
the Symbiotic Age: Speculations on Autonomy and Beyond

Working from simple log-periodic acceleration models like the
developmental spiral, we can argue that the Scientific Age lasted
for roughly 380 years (1490-1770), followed by an Industrial Age for 180
years (1770-1950). If these trends continue then today's Information Age
will last for only 70 years (1950-2020), and we can expect the coming
Symbiotic Age, driven by CI network and biologically inspired computing
advances, to last approximately 30 years (2020-2050). Beyond this, if
STEM
(space, time, energy and matter) efficiency and density of computation
and physical transformation continues at past trends, we can forsee a
coming developmental singularity,
should the structure of spacetime allow continued intelligence acceleration
toward the Planck scale.

There are at least two points we might make here. First, if this model
is roughly correct, the next fundamentally new era--which we are calling
the Symbiotic Age, will occur over a thirty year period between 2020 and
2050. Hierarchical developmental models almost always require that change
proceeds in a pattern known as "punctuated
equilibrium," brief bursts of new activity followed by longer
plateaus of consolidation, and where the final years of one stage are
always significantly slower than the early years of the next. This future
history we have offered, then, commits us to an expectation that the next
twenty years will be primarily a less-remarkable continuation of the groundwork
begun fifty years ago, at the birth of the Information Age.

Seen in retrospect then, the period between the emergence of the developmentally
inevitable Internet and its next necessary offspring, the CI network,
will not likely be considered, from the human perspective, as a period
of increasingly dramatic leaps, but rather of many steady, smaller, and
less noticable improvements, preparing us for the next great surge of
technological change. Borrowing a popular phrase, we can say that the
Symbiotic Age will require fifteen to twenty five additional years of
slow going and hard work before it suddenly and surprisingly becomes an
"overnight success" in the 2020's.

As a second point, consider the apparent dichotomy of the unprecedented
scientific and technological acceleration presently seen in first world
countries, and their decreasing rate of cultural change as they develop
ever finer distinctions in permissible social, politicolegal, and economic
behavior.Such deceleration of at least the magnitude of cultural
change in the first world strongly suggests we are rapidly moving toward
an end-stage, saturation phase of development in the human computational
substrate. In other words, there's not much more social optimizing left
that can be easily done by human beings running human societies. As Francis
Fukuyama (The
End of History, 1992) and others have observed, all the world's
governments drift closer every year to a scientific, capitalistic, democratic
final common pathway for social development.

In this new world the average citizen, having a sharply finite capacity
for change absorption, increasingly insulates their social
and cultural consciousness from the developmental hurricanes occuring
in the technological systems around them. Technological acceleration continues
unabated, it just increasingly proceeds "under the hood" of
the car of change, so to speak. Think about all the computation that went
into the creation of an advanced hybrid automobile like the Toyota Prius,
for example, and how oblivious we are to that, vs. car technology of the
1950's.

So does this mean that the total amount of socioeconomic change must
slow down in the Symbiotic Age? Hardly. We only need to lose our first
world bias to understand the unprecedented nature of the changes to come.
If billions of presently marginalized human beings are uplifted
toward first world socioeconomic status in coming decades, to a place
where only tens or hundreds of millions have gone before, this will still
represent massively unprecedented socioeconomic change for the average
distributed complexity of humanity on Earth. We can expect these changes,
given current trends, even as first world culture becomes increasingly
canalized (comfortably settled), social-benefits oriented, and regulated
with every passing year.

This new post-CI growth spurt of globalization will be tempered somewhat
by technological systems that allow us to increasingly preserve and maintain
existing cultural histories, and with less fidelity, cultural differences.
It will occur as human individual and cultural consciousnesses become
steadily better at either insulating themselves from, or balancing themselves
within, the accelerating computational change occuring all over the planet.
Globalization debates are today often framed in terms of how to help the
third world rise to first world standards. By mid century, they are likely
to be framed in terms of how to help societies of every type become more
change-seeking, versus change-averse, with regard to many powerful new
opportunities for human-machine symbiosis. "Symbiozation," not
globalization, sounds like the dominant cultural agenda, in addition to
refining globalization, in an era of late 21C economic abundance, to be
far more equitable and pluralistic, and in slowly demilitarizing a planet
that may finally have sufficient transparency and trust to allow flatter
and more bottom-up rather than top-down systems of global security.

If we wish to be acceleration-aware in our forecasting, we may not be
done yet. During the Symbiotic Age, the most successful of our CI's will
likely incorporate substantial bottom-up-developed biologically inpired
evolvable hardware (EHW) components, as well as a wide range of scanned
and reverse-engineered structural architectural elements of metazoan neural
networks within their differentiating body plans. Somewhere within this
process they will begin to develop high-level, scalable, and robust ability
to direct their own self-improvement, self-repair, and self-generation
(e.g., limited self-replication, variation, and selection of even high-level
neural architectures).

This vision argues that we must take a highly distributed, incremental,
and network-centric developmental route to the "Planetization"
of humanity, a concept eloquently envisioned by Teilhard de Chardin in
1945. (See "The Planetisation of Mankind" in The Future
of Man). The strong claim that I wish to make is that, just as linguistic
AI will require a planetary network of human beings, incrementally tuning
up the conversational interface (CI) to human-level utility, so too it
will require a planetary network of human beings tuning up all our robotic
systems to produce a broad collection of utility robots that are be sufficiently
situationally intelligent to interact in the human environment. This problem
is not an easy one. Like the CI, it is extremely complex, and robots will
be incredibly stupid for decades. Only the input and detailed, collective
feedback of their user-gardeners will allow them to become less than stupid.

Generally, I call this perspective the"95/5% Rule"and it's the idea that all major substrate transitions seem to
be primarily "95%" bottom-up and experimental, and only slightly
"5%" guided by top-down, hierarchical or developmental control.
It suggests that the primary role of the average 21C human being, from
technology's perspective, will be as a trainer and gardener of the growth
of tomorrow's intelligent technologies, just as we today are socially
constructing the wired and wireless participatory web.

Perhaps we will choose to allow various forms of increasingly autonomous
self-replication, with appropriate safeguards, because the adaptive machines
they empower will be natural incremental extensions of the machine learning
paradigms presently in existence, and because such extensions will demonstrate
dramatically greater human utility, as well as ever more self-balancing
and statistically safe behaviors in the vast majority of artificial selection
environments. But perhaps most importantly, our increasing understanding
of biological, cultural, and technological immune systems, systems that
were poorly understood by early 21st century thinkers, will allow us proceed
with growing wisdom.

As we begin to collectively train our machines, we can and should expect
that any local catastrophes that do occur (e.g., unpredictably behaving,
unsafe learning agents) will be rigorously contained by any redundant,
fault-tolerant, healthy immune architecture. We will come to realize
that those micro-catastrophes that do occur, within healthy immune environments,
can only catalyze immune learning, increasing the "average distributed
complexity" of the system, as well as general system intelligence.
This increasing informational immunity appears to be one of the great
hidden mechanisms that has guaranteed the accelerating hierarchical emergence
of computational substrates in universal history.

Within a few short years of this new self-directing, self-replicating
capacity, we will begin to suspect that our increasingly self-modelling
tools and agentsand by association, "we," as a human-machine
social networkare a good deal more intelligent than surface appearances
indicate. We can call that next era, an age of increasingly self-directing
symbiotic machine interfaces, the Autonomy Age. By comparison with previous
ages, it may last as little as 10 years (perhaps 2050-2060), taking us
to the edge of a circa 2060 technological singularity, in this very simplistic
model.

At some point after this we may expect such a high level
of integration with our twins that they become conscious extensions
of our biological selves. If the patterns of neural
synchronization which apparently generate our conscious perception
in brains can exist within both biological and digital networks,
as may very well be physically possible, then we could expect no subjective
cessation of conscious experience on the death of our biological
self. Furthermore, as our digital self will have both an indefinite lifespan
and the ability to backup and continously fork and reintegrate versions
of itself, no significant information destruction will have occurred
in the loss of the biological body and brain. As our computer technology
continues its accelerative and increasingly autonomous growth, these critical
patterns will have been progressively uploaded
into our twin. From the perspective of planetary
complexity, this would represent a major
transition in evolutionary development. An irreversible developmental
substrate shift (biological to technological) will have occurred, for
the leading edge of complexity on our planet. For more, on what might
happen next, see my 2002 paper, Answering
the Fermi Paradox, or its update, The
Transcension Hypothesis, 2011.

Greg Stock (in Metaman,
1993) Vernor
Vinge, 1993, and others have written eloquently on the coming
technological singularity. But few to date have considered the requisite
ethical constraints that must emerge naturally, in a 95% bottom-up, evolutionary
fashion, within self-directing technological systems that have many orders
of magnitude greater learning capacity than biological brains. We may
understand ethics as a form of behavioral immunity that protects an otherwise
precarious accelerating intelligence development, and no known intelligent
systems exist on Earth without the presence of a competent, healthy, overarching
immune system. Thinking about immunity, and helping it emerge naturally
as complexity scales, is thus one of our greatest opportunities and challenges
in coming decades.